This biostatistics research training program's goal is to establish and provide an internationally recognized predoctoral, interdisciplinary program that is strong in biostatistical theory and methodology, and also integrates biostatistics training with fundamentals in the biological and computational sciences. It is designed to prepare trainees for leadership roles in interdisciplinary research teams working on, for example, problems in bioinformatics, genetics, molecular biology, medicine and computational biology. The program will produce biostatisticians for the 21st century who have a high level of understanding of the biological sciences, a good knowledge of computer science and who can work effectively with scientists and clinicians engaged in problems that impact public health. The aims of this program are 1) to identify and recruit trainees from diverse scientific backgrounds and with strong quantitative skills, 2) to train students to master essential core biostatistics theory and methods, learn fundamental material in biology and computational science and develop solid communication skills - both written and oral, and, 3) to develop and establish a model interdisciplinary research training program in biostatistics that produces 21st century biostatisticians. It is well-known that the current demand for biostatisticians far exceeds the supply, and this gap is expected to widen. There is a critical need for biostatisticians who can effectively work with biologists and biomedical scientists to improve public health. Current biostatistics training programs cannot satisfy the shortfall. The proposed research training program addresses the short supply of biostatisticians by training 16 individuals, but more importantly, it creates a transportable curriculum that assures that the next generation of biostatisticians can participate fully in modern biological research efforts and public health initiatives, and that they will be adept at recognizing and making needed statistical innovations. This training proposal represents a cooperative effort among scientists from a number of disciplines including biology, computer science, psychological sciences, genetics and health psychology. The key components of the program include (1) formal course work, (2) rotations in biology, computational biology, statistical consultancies and in medical and behavioral research units, (3) other interactive venues including seminars and journal clubs, and (4) dissertation work.